Measurement‐based dynamic load modelling using time‐domain simulation and parallel‐evolutionary search. Issue 15 (1st November 2016)

• Record Type: Journal Article
• Authors: Zhang, Rui; Xu, Yan; Dong, Zhao Yang; Wong, Kit Po
• Is Part Of: IET generation, transmission & distribution. Volume 10:Issue 15(2016)
• Page Start: 3893
• Page End: 3900
• Publication Date: 2016-11-01
• Subjects: power system measurement -- evolutionary computation -- search problems -- load (electric) -- wind turbines; measurement‐based dynamic load modelling -- time‐domain simulation -- parallel‐evolutionary search -- power system analysis -- power system simulation -- wind power -- fault‐induced dynamic voltage response -- measurement‐based load modelling -- industry‐grade software -- fitting error -- trajectory sensitivity index -- parallel‐differential evolutionary algorithm -- real‐world filed measurement data -- optimisation model; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2016.0579
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Conventional approaches for measurement‐based load modelling uses measured voltage ( V ) as the input to calculate the load model output – P and Q powers. This assumes that the P and Q response is a function of V . In fact, there is an inherent interaction among the three variables ( P, Q, and V ) especially when motor load occupies a large proportion. With increased penetration of wind power, the fault‐induced dynamic voltage response is becoming a serious concern given the low‐voltage‐ride‐through (LVRT) requirement of wind turbines. This paper firstly shows that given different load model parameters, the V responses can vary significantly. Then, an improved method is proposed for more accurate measurement‐based load modelling. The proposed method incorporates the V response into the load model output, therefore is able to accurately reflect the dynamic voltage trajectories. Given the load model parameters, the system responses of P, Q, and V are all simulated via time‐domain simulations using industry‐grade software, and problem is to search the load model parameters to minimise the fitting error between the simulated and measured system responses. A trajectory sensitivity index is used to identify the well‐conditioned parameters, and a parallel‐differential evolutionary algorithm is designed to solve the model.